{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    mpg  cylinders  displacement horsepower  weight  acceleration  model year  \\\n",
      "0  18.0          8         307.0      130.0  3504.0          12.0          70   \n",
      "1  15.0          8         350.0      165.0  3693.0          11.5          70   \n",
      "2  18.0          8         318.0      150.0  3436.0          11.0          70   \n",
      "3  16.0          8         304.0      150.0  3433.0          12.0          70   \n",
      "4  17.0          8         302.0      140.0  3449.0          10.5          70   \n",
      "\n",
      "   origin                   car name  \n",
      "0       1  chevrolet chevelle malibu  \n",
      "1       1          buick skylark 320  \n",
      "2       1         plymouth satellite  \n",
      "3       1              amc rebel sst  \n",
      "4       1                ford torino  \n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "columns = [\"mpg\", \"cylinders\", \"displacement\", \"horsepower\", \"weight\", \"acceleration\", \"model year\", \"origin\", \"car name\"]\n",
    "cars = pd.read_table(\"auto-mpg.data\", delim_whitespace=True, names=columns)\n",
    "print(cars.head(5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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YSJG2tjYxpkDizR3GFMjLL78c019v0T7WPDTeOd4p1gwz3hEwWiRqknE1IHmS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\nq6GLKQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x64eb690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax1 = fig.add_subplot(2,1,1)\n",
    "ax2 = fig.add_subplot(2,1,2)\n",
    "cars.plot(\"weight\", \"mpg\", kind='scatter', ax=ax1)\n",
    "cars.plot(\"acceleration\", \"mpg\", kind='scatter', ax=ax2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import sklearn\n",
    "from sklearn.linear_model import LinearRegression\n",
    "lr = LinearRegression()\n",
    "lr.fit(cars[[\"weight\"]], cars[\"mpg\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 19.41852276  17.96764345  19.94053224  19.96356207  19.84073631]\n",
      "0    18.0\n",
      "1    15.0\n",
      "2    18.0\n",
      "3    16.0\n",
      "4    17.0\n",
      "Name: mpg, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "import sklearn\n",
    "from sklearn.linear_model import LinearRegression\n",
    "lr = LinearRegression(fit_intercept=True)\n",
    "lr.fit(cars[[\"weight\"]], cars[\"mpg\"])\n",
    "predictions = lr.predict(cars[[\"weight\"]])\n",
    "print(predictions[0:5])\n",
    "print(cars[\"mpg\"][0:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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e5Kqr3k1bW1tkZc4gcX2xbDv23JVUUXJqaopcLkd/by/9vb0LCpcJIVY49Zra\niNrQUkXNiBPwVVscWSgUzOjoqGlzp/zbLMuk3GMHwKzHEWam3T9zYNYWlzI8N0VHyPKF8YkrT7pO\nDC+tdcmJYVnWgnYHlxXy+XxkX7xU1idxXCnbwLzLbWvGtk2bbRd1IveBGXG39WD6stnY38FyWt6Q\n6FOI5YU0DqLqxAn4wuyY/sE3yTW8z7szGSdgcIMCr7CVf/CxwXSk02ZsbKx4ra1bt3pf+qKbItxp\ncVMZJ0aqqKUYHh4utic4+OXz+dC++PvgOVDaAuf3g7mF+XUy2tzPwgbV5TgIrwSbqRCthAIHsSzx\nMkp6uSOi8ki04RS38g9A3kB1EL+QMpgLos/Anhgnxj7j5ImYXxfjoQoHP2/W4e6I9nvBT9JBdTkO\nwq2eEVOIVkPiSLEsefLECVZTqlTxFcKrVuSA1ThiQ/+5OZz8k/uAaWb5bS7TwTiOiHIWuAonO+Wb\nMa3Iunfox1EfWHyMFL8LvMF8oaMf/3r+4488Qg44HdP+/oj9wev6+5b0eCGEWA4ocBBNRTdOOtIZ\nZplmluuZA57DCai/RXxaaw9PUJni90nRR5qPABcD9wo6JVbVqE/LiUrFsEKIlYcCB7Fktu3YwavA\nBM4g81Hfzx7e4PMq8wcgb6Da7DvnDRwb507g+8Dg4Bry+dNs3boFJ4DwOzGGcYq1bmVhALEK6GeO\nD/AwNg+T5rXpN9i6dStTU1MLnBK/heP+8LclrP1JB9XlMgj7Z11OPv44qVRKNSqEENHUa00kakMa\nh6pSbxW/56bwHBNelsowcWQajG1Zpi+bXeB0sCmlxA4TJnqCwvvuu88novRX50wb2OgmkTrjaiNu\nNNBrFtbD8ISUtrmRUnIsL1W3HdP+AfdPTxyZBtOeSs2r5+H1bXJy0qTdmh5+Z0kl4sha/z7DBJw2\nmHQqVfw9KSOmEM2LxJFiSdRbxR+WKdKzYGZdsWMxoEilTJub5jrK6dCXzRrL3R8nKJycnDSpVMqU\nUlrb7s97TCnb5Ho3QGjzuTCmfeLJ+YW11oF53g0eitZRd9BPu/tyrmjyPWCGwbzf7WfKDR4WDL4h\nwYcXZDTL73M5CjiFECUUOIglUe9BIOp+bTh1MvwVOZO2rRJVfz6fN/39/W7QkHKDgAE3OLBdN0bS\nwlrOLMQtlJwfcf27xg0i9rpBRfC4uxMEQIt9vtX8fcpFIcTyRq4KsSTqreKPu99Dvp/Pv/RSTdq2\nYcMGXn3TNpDeAAAgAElEQVT1VYyZI59/hjVrrgBew/FoGODawBlRfo89wBBgeAabOWy++tWv8tjX\nvx7a5t04pWGfwtFG9LtX8B93mvAcmJX0V66MpaMsmEJUHwUOoqlYrKBww4YNvPzyyxQK/8jIyDac\nr/ZZFsocw3gHeAmwcUKAPczNpXjr7VlO4AQJQVYxf0BfLI0e2JaLgHMxqL6IEDWiXlMbURtaqqga\nrbBUUa11/Xw+b6644gqfiHKvT98QXKoIaiGMcdJbl0SUHwJT8LV5va8fYQmvkixVlOtrPX6fyzG7\nZVKk3xArAWkcxJKIGgTiBHmeK6I9lTIpSrUZRkdHyw4cUffrxxES+mtfeFkZw9JQA8Zyf7bB9PX1\nmVWrVhWPHxwcXND+KLdBcP+WLVuMbdumJKL0Z6bc5/6cMfMzUk4bpyZG0I2R9v6BmpRvQPIElUnE\nkf4BudzAVq9BvVxK8eWK9BtiJaDAQSyZfD6f2AJYKBRMd0dHpAWyu6MjUfDgDTq9XV2mvb29OGgO\nDg6aycnJ4uCX8w2wthsseC6M4L2948MGy6gBtbujI7JGxeTkpFmzZo0rpLR8AUTWwJpA4JCkJoZl\nAPMhf6AQsDBG1cXwSDKwteqgXg8UOIiVgAIHsWQqmZ71jo2rzbDUKd2o9qTczY659/0RbYnrYyph\nPx588EFTcmOkAoFCVE2MvcZxbfhnIJwAYmxsrOIBXQNbbdFShVgJKHAQS6aSwcg7dgQnmVEtBrCo\n9gz4tsh7u227D2f2wWtLXB8HKuhHPp83Fv7CWt4ShhccBC+1zw0qjG8GwktGZZvh4eHQRFBRAYUG\nttrSyvoNITxkxxTCRxpYA9wLPAnMzc1V9fobNmzghUKBNmuOfi7jFNQaB14hOum0l9LaM0amgA8A\nnZw69bds3HgzExNfY2h6mtvKqPgPHz5MZ2dnMb3zHuBW97NvPPbYirQOVtNlMjQ0xHPnzrErl+N4\nTw/He3rYlcvx3LlzDA0NVbnlQqwg6hWhRG1oxqGqtMpShefM8LdlcHCwbB+TLlWEtfGvwdyOV97b\nPwPhLU3cahzhpHf5nIFuM19E2Wag34Bt2rDNQbePUff3NAx92WxZMWWroxkCISpHSxViyVTyn29Q\nHBkmNvQLEstNwYcd49Wi8Kel9jsoPHFk8N63Uqoh4S039GWzRRdI2Dlx4si4tnrt87fR+YdYWoZw\ndBAnfUFDlI3Tq5NxyHhiyhS2SadSsYNfWDB00n0+GduuS92RRqOlGyEqR4GDqAqVKPELhYIZGxtb\nYMf0i/2SBCNxx/hrUYQN+FYgmFgfCBr8gUOYQyNNSZyYpO/+tnoFubz7DvgCGsB0hc5A+G2ccVqI\nnPHnggDLDA8Ph/4ugroNr+BWVLGvVkRiUSEqR4GDaEqSvAku5Zg2d6AulyhqcHCwKm+k/nuEJW86\n4wYPg4ODxQDEyQXhF1Je6QskwgKHbe6SRXC5w5m92L59e6w1M6pdrfz2rcBBiMpR4CCakiT/oS/l\nmH2UylXHzVz0ZbNVGVj87UjqKPHaMw3mt8GUbJxhmSjb3BmHsM88J4YzC9Hf3190YviDolo6XZoV\nLVUIUTlyVYiW4g3ge8D09DT9vb288dZbXC5zTpwSPpVq/Ne1G/gcUGCOHuZw/r16voh97s89OD6Q\nqBJVpZoY589fYOPGzbzyyit0ZDLFK3llulYSQZeJ9zQ7Ozt54IEHGts4IUSRxv9PLJqeJIWQgse8\nAWwFnsUZKndOT2NmZ3kYeCLkOq8C/YODgBM8jI+Pc/7CBc5fuMD4+DhDQ0NVK8jkv85HiTZe+q+5\namBg3r2HgP8VsJjlPVzGsXGOA3PA20BnTAs24NTV/DLwNACnTn2TNy69g7FtJjs7eS2ViuzrrVu3\ntmTFR9knhVgm1GtqI2pDSxVNz2LEkZ5wMcoyGUwvbUNkPY1K2lFpfzxxZLlr5vP5BcJOfz2KHJgb\ncZwYVjElddRSxf2BFQgv6VSbmV9TwxGN+tuVzWQSO0eEEK2PlipEU1LuTXBqaooDBw6QSqWwbZsJ\n2y7ONIRN1Kfdt+mjOO/nV6xZw19PTnLPPffEvkUPDQ1x8qmn6B8c5CjO+32qvR3LsrjhuusYHBzk\niu7ueeeHJRQCitd5GHjdvc6jXV2Rb7mDg4Ns3b6dObfd40CqrY2Ojg7mgFM4yarux3CBWZ73zBhs\nAT7ubluAPuCXA0/YAm5wr+L9vAdIY7A5B/yD+6w6e3q4eOkSTzN/zmJmZoa77rqr8l9ujWl02XAh\nRA2oV4QStaEZh2VN1CyA9/ck4r6kMwlJZgr8lTm7MxnT3dGxMN9DxP6ot/Zg+/yVP70012F9HcWf\nC2LAdWLYEWJKbxbCs3JOG/h3xm/n7PLNQIQ9V09c2iwooZMQtUeuCrHsiMsM2RaxVBGVwbLcsVE2\nymn375t8ywZe8qSotlWi3g+2L2iVjLNOjo2NmbGxMZNKtfuCAL9Fs83Mz0jpWTlvMaXcEevdwMNx\nZGTAPB8IHPbFtL9RyCUhRO1R4CCWHVEWyxyYPjd42Ocb2MLeipP698NslF6ipHb373vde94KZk3E\n23nUDEGU1THYvqBVsgDmGrdvcaXMC4WCGRkZMfPLeh/yBQ3e7EPO/bzNDRra3YDCSzzl5IL4kHtv\nLxfG+oj2NwrlZRCi9jQicEjXf3FErATSwHqclf2H3H3XAz/OZquqkP8icBZ4ipKe4hlgGGiv2l2i\neQNHjfASjn4DHA2EnUpx8qmn5vV1aGiIEydO0N/bizU9zWvYGP4Q+IHvzOuB80A/cCXwHAt7twWY\n5XFsrsJxdtwMvAt4oYZ9FUIIkB1TLJE4i+Qw8JvACeA/41gzR26/vaJr+C2RYTbKI8BuwkWYF91r\nBK/7asT+KFtnsH1+C6c/cPGLFefm5hgbG4sUAl4F2MwyzGXseVbOZ3GyXwC8GNO7NPAR4AYMaZ7B\n5ihw0803h96vEVTLPiuEaC4UOIglEZW0B+C/sDCRz2c+85l5KvuxsTGmp6fBPeYmnDf4sMQ//nsd\nx0nGdBZCEyUZHH9CR0fHgrZZQCqVWrC/o6ODixcvznMAnD17lkuXLs1r3zHgsvv33wF+mvCh/fxL\nL4WW1N62YwffxZlbOAN8lFl2Met+Oge8hRPevBbz5LuAKZwgYw+eC+Mb3/gb2traePTRR2POrQ+t\nlNBJ7hAhfNRrTSRqQxqHZU9YYSmvsFVwX5w7we/I8BfZirpXXzZr2tvbIwV43jXGxsaK113v3tcG\nk06lTF82a1b19JixsbHQ/Ahejomw3A1xjop9+MSaASGg5zYIFtaywPxbML1FEWVUSuu0gRtd7UPY\nZ855lmWb0dHRhjoYKim41qzIHSKaGYkjRUtTzp2wGNV9kv/Ul1qk65Bv392QqA9tYO6PEQIGB9Q1\na9aYNCUx6RheIoigC8OryjnsiiWDMcs+A5vmBRBgm9WrV5dNsCXCkTtENDMKHERLU86dsFjVfbm3\n2qUW6RoJtDms/LUXuOyj5OqYrqAvq3p6TM4NNkbc7X6cvBRrwM1G6VXoTLvBQVTgMOILINqMvyBX\nsCqnKI/cIaKZUeZIIRZBVG2LetANPAasxhH9/QinCNZjOOqDpELAubk5fkDJgfJRnPySNrAdmGOW\n55mlp/hP9ltESzw/5v49i6O2WA04osmTJ5/kXe96L2fPnl1EbytH2gAhWg8FDqJuxLkTPGqhul9M\nkS7/Mbf69m1m4XD9PeAVHMHlWeAk8K9JLgScmppiZmaGZ3HSVq8B7sUpEvaK737vB15gjoNchgWV\nOT+O42PZ6J7pDyDACSI+AlzJ3NwsGzduwrJSpFLtse6PpTA1NcW6tWs5NjHBzulpdk5Pc2xiIlQw\n2szIHSJEgHpNbURtaKlixVAudXNS0VmhUDCjo6MmY9vFolme0HH37t0Lzi0UCuGppzs6Iot0JRVH\n+tscJgj1X3/37t2mt6vLpHzXGRgYMNu3b49cQ7d89/OEnV7a7K1bt5pSSmsvw+QeU8pGedK3VPEZ\nA/0+vUTO3Z8pCjEnJyfntdXrR9gzDT7fsONbRRsgcaRoZqRxEC1PUI/gpWROqroPCwLa3P/IVxGd\nsbE7kzEpHAfDgBtsdGcyC45L6g6pxCngd1H0u+0NBie5iDX0JI6TyclJ09bmVdb0AoicL6C4xTh1\nLzyHxrQbWLQHRJeOkNJiYQXTpHU8/Mf3ZbMtow1oBXeIaE0UOAhRhqi32DZ3sDsU8kbb6Ddf7/53\nE+0iWR8xwG6qoM2e9bQUQKQM3ODOQngzDcbAfSbayrm+GEB8iFJK66R1PPztzNh2ywQOQjQrChyE\nKEOUwn2fO5MwEjIwVaKKr9Y0vf/zNts2A+6MSFxly7DB9/5FDLqFQsF0tbe7/5l4QUSPL3DwXBfB\npniOjJPGX5WzD8w6MH3ZbOLfx14wbe5S0nJfqhCimVGtCiEaiCfmm5mZKdWdcMV8z507t8CpUe54\ngHVr12JmZ7kNeKLM/bcwv95FL46zolKGhob4/o9+xMGDBzk+Ocn0zEXgTRbKOsOYBe7G8XPsBuB1\njvI6wJtvcvbsWTZs2JCoHV0dHczNzbHF/3xYnpkjhRA+6hWhRG1oxkFUQC2XKipd0ih3fCUJr9as\nWTNvDX1wcNDYVXpbL1Xl9Iso20KWKrzKnHEZKZ1cEl5CqXLPQNoAIWqLlirEiqDS5YDguWEOiTSY\nDjd48BwO3j36slmTTqVMilKK5zSOE8PLplgoFGLX5DO2vaC95ZZAgp8Hk0V5bbfB9HZ1zbt2lOiw\n3Zcm239skueZz+dNf3+/KWWU9Gek9JwY22KWMfwZKZ1ljFtuuSU0VbccB0LUBwUOouWphrWtUCiY\nnTt3htoU21OOrTB4j3I2Sv/xURqESl0DYYHFtNterz2eNTPsWQTrcqRTqQXHdmcy8wKpnHvNNMTa\nU50ZCKsYADjBwB4DAz4tRDBw8LQRXvCQMmCZ9vauipwxQojqocBBtDzVcjjEXWdwcHDBZ8EaE2HH\nx7keDiW8T9xSRaWfJ+mvFyScoTSj0V5hUDY5Oembhcia8MJabQbudwOHAd9mFwMQ2840vKiWECsN\nBQ6i5alW3v+464TNHARrTIQd7w28XqEp77N+97PgeX3ZbOzsSbnZlUqeRdSx/uqcSYuGhS1t5PN5\nN6GUtwzhLWPsMwsTSt3kBg1rjGfddGyfXb4ZDMvYlmVGR0fN5OSkGRgYKM74DAwMqOCWEFVCtSqE\naCBe3YnP4aR6fgInsfM297MgqVSK586dY1cux/GeHo739LArlys6MIaGhmI/rzZfwfFB3OLbdwuO\nU+OJ48eB6DTQ27du5ctf/jKFwj8xPHwrjrti3N2uB64CbgfWAd8FXnU3A3wAeB54Gyet9Q2Azayx\neeSRRxi9807Ov/wyObctr738Mps3bqxbvQwhRJWpJMoA/g/gaeAC8CLwZWBdyHGfBl4A3gK+DlwX\nc03NOKwgmnmpotLPFuNu8L/pDwwMJHJOFAqF4hv7JndmYZqFSxXbwNxEqbqmd5x/BiPp8y8UCr4Z\niLQ7w7DeNxvhz1JpuzMRJ00pI+U+489IOeybtfE/20qfWSVCWiFWAk2/VAF8Fad+z43AT+LYsn8I\ndPqO+SRwHufl4ibgr4DvA+0R11TgsIKImr7vzjjr45UkXopyHSxGHBmVkjoonFysmHN0dDT0/p6r\nYl47fc6J0dHR0BTb/e6xnjjSBpN1r7fP3dopCTHbXFdIuWyO/oG6L5s1aec/JF9Zb8sNJjx9g6d1\n2GvCM1LOTyaVAnMnmF1uWxfzXfE/ewUWYqXT9IHDgpOdQn5zwHbfvheAQ76/9wIzwM9GXEOBwwoj\nrF5FmMWy3OCcz+dNOpVy1s19g2RUwamoGhPlimAtJReBN/il3AE/albDG6jb3f547fDPKISd57Uv\nbmYkheO28JwnUYFDULOxPnDvaTC/CoZ5QYQ3G7HXLMxI6dXEaDMLa2JYBojVOiTJEaHiU2KlsxwD\nh+twFkN/wv37tW4gsSFw3OPA5yOuocBhhbPY5Yt6LHssNTWyd+1N7ixA1Jt+VDs2BQb6aZwlCC8X\nRZKcEje7P9/nBlZRAspg8DES0+a+bNZkMt2mZMtsM06eB3/gEFUTwzbQbbwlj+Hh4dCBvpx4tNE1\nSIRoBpaVONKyLAv4AnDSGPP37u4htwMvBg5/0f1MiAU8eeIEOeJFfdU8r1bXibt2dpHt8J/3Bo48\n8V7gNrd9x9wU13Nzc5HX7XH//Arw08AGYBj4uLttcT+/9OabC+4fRSqV4oc//B4jI7e5ewzwLean\ntQ6Ta34A6AMuAnuAPZw6dZprr/0AU1NTCe5copa/NyFENOklnPtfgZ/A+T9syRw6dIi+vr55+/bv\n38/+/furcXkhGspHcQb8ZygNdM/gDLO7du6MPe8e99hJ4CzwVOAaW2Zm6B8c5Oibb4Ze/z/4rpfG\ncY78CfCQu+964MdZJ0T5HrDD3d8LTMS0eWhoiBMnTjA1NcU1V1+NMYY5UpSqbnyXhf89fBGYxtFY\nl6568eIWrrnmPXR1dbNjxzYOHz7Mth07ODoxEXn/pMHB1NQUBw4c4MkTJwDYtmMHhw8fromzRYha\ncuTIEY4cOTJv3+uvv17/hixmmgL4I+BHwHsC+7VUISpmJSxVnCQ8R4R/PT6sHScpiSj9ORvK6RP8\n4suTvqWKqGWKsbGxor7CE1e2URJcltMQeMsKBTAfwdNBeBoI/1LFJhOemXKvgdWuXqIkpgRHoxGW\nFTOJK0U6CNHqLAuNgxs0/COwNuLzKHHkz0Qcr8BhhbPY/9yrNSjUcnDxXztHSXDoDdbBEtxRjpOx\nsbFYYaPniFggOvXVkcj57h3sp+f6CA7CNhjLHajjhKH+AOk+N0gKr4nh/RwWOLS7nwfFlHZRvFrO\nlZIkGJMOQrQSTR844CxPvAaMAFf6tg7fMb+FkxlmD45l869wZkBlxxSRhA16o6OjjgjPtk2bbYfW\nXqhW9cWw6/gLZS3F6hfVxqCVcHR01Gzfvt202bax3bfrjK/fUYN73CAY9lzD6krECRHbUymTtu3i\nIJ2iZBn1F9rygpQ297xdzn9m7laaQQivzJku85mT1vqD7qyGv+8pKH4/gr//amUqFaJZWQ6BwxyO\niyK43RU47lOUEkAdQwmgRAWEvXn7cxfUY5q51lPcwev7ZwNybl/DZh4WY1tNQlzBLn8w4H/TXxX4\nfcTNWuwAY7tFscJnIdqN47SImo3oKR7bQboYPOyl5DCJW0JR4CBalaYPHGrSAAUOIkDU9HIbTrGp\nekwz13qKO3h9v/6gnBahGjMsQbzMlFF5IKL2+38fcYP0iPvzNJjPgOksVub0ZhN6DGRiAodVxskL\ncXdx+SKDZQbAvJeSFiRpcTAtVYhWQYGDECb6LXEfpWJVtX5brPWbavD6/pwJcfkTatXvvmzW9FMS\nb3riyAzODEhYWwYCv4+4Z7YpYuAuFAqms7PHlDJSRi1VvNeU0lkvTCbVDWYUZ2kniW5kqbM0ylgp\nmoVllcdBCNE6pFIptlEq8PWK+3MPyT3b23bsmJfFAUr2yW8B+9xtC9DZ2ckDDzzA0NAQ5849x9at\nw1CURPizTAy7V7qRkhn1y+72tPuZxRukeQSbS7OzvP+97y3mhKhFobGoQmHr1q6tOBeFEMsRBQ6i\n6YgbgG51/7wtJvdBrdtQjXsHr/9RSjkT/D/X4t5hbB4e5qvAX/jasxWn6ExUW15l/u/j8OHDdHZ2\nsoX5QQI4gcnXbJvHstkFA/fQ0BCrV6/GwtBZlFGddLdZnAS1Fwiv/bkHuBmwcIKOFG+9PcdVV13F\no48+Wrz++Pg45y9c4PyFC4yPj4cGDVNTU+RyOfp7e+nv7SWXy4UGAgcOHGBmZoanmR/CzMzMcPDg\nwSSPW4jlTb2mNqI2tFTRElRz6jZqenk5iSM9sWCb60bI2LYZHR2dV5ypUnGkDca2rKLTYnR0NFFh\nMO93E+VQCavV0ebTMUTZILvcz4NFp3K5XLFAllcnw39eOpWa5xbJ5/PF4lvTYO4HM4xtOrFNKaeD\nVw8juBKyz5RqZAwYJ0+Ep5tIm46O7tDnEuZoSSo8leBSNBPSOIhlSS3Wkf0DkH+wq5YYsJI2VCpE\nDLMmBgtnhV3fs0r2ZbPF/Ale4qcbKVX4DA7guZhnnsShEmfz3Llzp5NDIpVyAhc3YLjB/bk9lQot\nVBUnSkyF9MHLxeAfiKfBrCuuX4QlkzrjaiLu9wUOI26A0ese79TE6OzsiQzayhUTC4ooFTiIZkKB\ng1iWSLk+n927d5sU0c6Ics8k7Pwop0Wb+4Yedf0kDpVypbbjrhPVn7DBdRonAVYPmGvBvB+nAFcK\nzLaY53XIPfemogtjrxsotLmCyZPuzyk3iPBcGJ6A8r3Gn0eip6dnQcbJYDGxuGBA33fRTChwEMsS\nvYHNZ1VPjxlg8c6IsPOjnBae0yTq+kkcKuUyUsZdJ6o/weOncbJJektO/pmYNjC9YDaycIam3z3X\nu8Zv4yWTShtYbyBnSu6KW9wgIu3uHzXhOSPSBlLm3WD+vXtd71mE9S9j2/OWg/L5/JKXsRazrCcn\nhwhDrgohRF25jJPVrdpC0KD484s4nohP4FT5PEVJWHgKJ1Pcy25bnnC3OZz/DT26cZwee5jlPVym\nj+8CD7tHXge8C/gQ0An8OvCIe2ZQxghg+EdS/A5pekgxBYxHPIN3ZmfnuSe2b93KyaeeWpRTY7GO\nDDk5RFNRrwglakMzDsseTd3OZzktVaRw9AXrmZ/DIY2jX1hszYegjsAr0BWXoyLq+odi+vzXeBoI\nbybhSgO7AjMNwdvtNU6yKU9Iub54fJj+4mQVv9eNLugmWg8tVYhliSoQzscvjlyQNtonjqzk/KgC\nVZWII/1FtjI44ktPlOi5GUbcbT1OYauw6/jv3+7WrAibOg86LMoFDgMxAUW5Pv/pn/6psSwvG6VX\nE6Nc4OC5MUbcJY5SVU7LDUhuoLRUEmxTpUsFhUIhkZ4kDC0HiigUOIhlS7WKTbUKhULBjI2NzbNj\nBqthVnJ+GseK6bcyRhWsirpWXOCRZEDy/477stmi0yJJsLhjxw6TBnM30TMx6yPa4dcYhPU5qDnw\nym+XgoeoolmeG2ObcUSWaQM3Gif9ddoNJDC3BIKHcvUxon6f/jbWO3CQPqJ1UeAghKgJ5eyRtZ46\n9yyfaTCrQwKYdjcIWezSTlhb5i9hBMWRG0zJjZFz/7zRzC/p3Wa8uhjXkDL34SxbeEsllSwVeG2M\nC5xqtVShGcHWRoGDEKImxL2xhs1ElBtUFuOyyLkD7jZKdsw1OCWxl+JUiGtLV3u7bwnDm2lY5wsW\nbnVnHG4y4XUyPJtntnj+Bt8MRM5tf7k3ea+NnrvE05Mk7edSBv+4oGNwcFDBwzJHrgohRN3Jummg\nq1XLIYo08Js4jolzwPPAdqC7q4sNGzZUvaYEQCaTYW5uDmMuUyj8Izt37gC+j+PGmAWGgO8BLxKe\n0joHrMZxatwA2JzF5hrgt92+mIDrIs7p0A08RqkmyBOAZdtl+7mUmhtPnjhBLqJn5196Sc4MUTn1\nilCiNjTjIETNqbYqP8n1/OvqGds2KarrUFhs3wqFghkZGTGlbJTen1EprdcY6DNOZc59JliZM0mf\nGumKiMvlsalObRC1Q0sVQoiaUI3aGwtqO7jOj7DrRd0v7S5PrGdpdUf87alUqBk8PwXGImWiU1pb\nEcsYTuCQwTa7wRRilmuSPP8wAWM+n5/Xz4GBgQUulijho7ffE9hGWXnjBJbVEFVKmFlbFDgIIWrG\nUmpvhA163R0dka6OuDdszxJqg5mcnFxUP8pZQ+P6FpZjYhRMz7yU1v5ZhV53psEEtr2mVHzLOXYU\nzK6IgTju+Yf1yatN4jlfwgqfdXd0hAZw3ZlMsWhX8Nx9btBwK47mIipwqIaoUsLM2qPAQQjRdCxm\nmr1cqmu/OK8e7Yk730uudRLM74FpK+aCSLmzDTdHBA5eDgjjm4FwZi4sq62iN+uwPt1NKSlWVAKw\nKFdMsGjXNKXaJNfgzDRMl3lu1VheUeKq2qPAQQjRdCwmh0C5wME7Pw11aU/c+f46GvPzQHhujFTE\nUoVXmdMfSHjZKK80/qqc5abrPdfJfZRcJ104yzrevkoSZ60hOl9E0rf/aiSdUuKq2iNXhRCiJQjW\nqoBS7YePNaZJkXhOh+tx2vdETw8/nctRKLxAPn+GUtWMLcA+d9sCbAR+OXC1LI5f4W3gaWZmZrjr\nrrvK1pmYm5vjSeAe4Fngx8C/wHGd3Av8fzh1RZLwBjAd87lt2zV30IgWp14RStSGZhyEaGoWM90c\ntrbtX1dvpqWKcuePjo4awHSDseYtY5yMmIHwynobA3tNKtVuwCknnsI2GWzzQXdWw7vfwMBAbIKo\nNohMkBVcqrjb3bfYWinVes7VuoaIR0sVQoiaU6nKPU7g5lf9BxX9o6OjRUW/7fzHZta4U+teca18\nPl9xO8sJ7oKOC78TYXR01GzZsqUoPCx3/qqeHrN9+3bTnkoVj99FMCPlPlNKJuUv623cP1MmOoNl\nyqxZs8ZkM5mytTwyIW32iyP9tUhyzE805RUuS0c88yhHh8SRzY8CByFETVnsf+RhjoCogSWo9I8q\n0JXNZBI7H8IG9zCHQrCoV5gTwQtk1lOqOZFOpUw+n19w31zE8fNrYXgVNnPuzz0GCu4shCewjKqZ\n4VXmtM0HiNcyeDM0QedIsBaJV4k0rHBZmAW2XGC41Bo0qmNTWxQ4CCFqSjWnjpPWv4hzBETdsxrl\np+PuGyzV7V03ynERla45BWYHmG5sk8J2g4RdgVmFjIlOLjVi/DkhVmObthr12yulHryWlhOWNwoc\nhBA1pZoq97hr+ZX+cdPvlboyKqkiGXffkYjrBu8bd42+bDaiKqdtstk+k8vlTDbblyBwMO7nV5uS\nkzLajmAAABdASURBVMM2AzjLIklmhPzt9tfDCNOXBJ+hnA/LG7kqhBBimZBKpebVjyi5MX7MG2/8\nM+Pj43zoQ9txHBZJPCYvATawB9jDy6R5mDSbh4d57tw5AHK5HP29vfT39pLL5UJrTPjrYTwBHHd/\nfsz9TIglU68IJWpDMw5C1A0tVVRvqSLJ8yoUCqa9vcuwICulJ6acNvOTR51x991nSjkhnAybcZqP\nuOcV1ddafCdE/dFShRCiplRT5R6XijqJOLJcLYnFijiTiiODbQ5zbCym7WFtGh4e9i1DZNwgIecL\nIjwnxrQbUIQV1EqZuymV9PYP7nG1QcrV8JDzYXmjwEEIURXiLJfVVLnHuRv8+8fGxiLrWlRy7Tj7\np9+C6bkP/D977RgZGSnaRDO2bcbGxhYMpEtte9jvoi+bNbZluUFDyjjuizXuz7YbJNznBg1hDozr\njefQsLDN9Tg1NtI4eovR0VEzNjZm+rJZk7Ft02bbprery6xZs8akXTtpe8qxf/rtqaOjo6YvmzVt\ntl20nXp22YGBgVjLbJI+t9m2ydi26ctmVeCqBjQicLCMM3g3DMuyNgGnT58+zaZNmxraFiFagamp\nKdatXcvMzAw5d99RoLOzc1lnCYzqV0cmA5bFxYsXm66/YW0eB9qAy9huNkgvM2Ua2AC8F/jLwJU+\nDky4x/p7CR1cZhR4GOjo6ABjuHjpUuAoGAWeBi4suALswslM+Yj79+Dnp/N5NmzYUFGf35qZoQ8n\ni+Vu3/Wa4ffSSpw5c4bNmzcDbDbGnKnHPSWOFKLFOHDgADMzMzwNfNndngZmZmY4ePBgYxu3BKL6\n9dalS1y8eLEp+xvW5m8Cs8B/YJYzzGJjKP1XfBYniAhicIKGYC/hIvAoNr8EzFy8yFuXLi04ysIJ\nS94IuYIFfAhHlknoHWBsbKziPv+ae79TNN/vRSwNzTgI0WL09/ayc3qaLwf27wOO9/Rw/sKFRjRr\nyUT1axC4DZqyv1Ft/jjwCnACp53fwJlreAxwhvingVvco5/BqY1xPfDtwJX24bzH5/DmB9q4zD8A\n/vf5jwOP4wQIYXMZr7hX3kn4czwKvJNwrPD6/CqwJuR+zfB7aSU04yCEECuQFPAoUACuXlBQa9g9\n4tqIs22c4f5xYI53sLmKNGPAQrOmEEtHgYMQLUZcZcrbdu5sTKOqQFS/XiU6S0Kj+1uuSugzOMqF\n8+7PQ8CzzHKIy8A4acZxFjb6cFQMYVdai7MocDelPBC7eIQUV5HmSmwewgk/JmLaso3o59g/OFhx\nnzfH3K/RvxexROqlwozakKtCiKqSxF5XaaGrZiDS/pnJmO6OjrJ2wnJOk7AiT0s93qvnEax10ek6\nIlI+y6Tl2j+99vd77gbLMqV6F8FCWe0Gng+4MTxLZ5txamEMGC+ltUWp7kbO/TmFU3xstfv34HO0\nwfR2dSX+nni/JzvCDpvNZMzo6GjRAbNmzZqim6PNts3o6GjTfReb+d+L7JhCiKoQZ7lczr79pPbP\noGWyXCGn4GfeAJr0+LicCZOTk/Oqa/qPD9vXnkqZNte+6PUjn8+bK664wh0g0q59EwMPuZbNETfv\ng3GDCC9o8PJB7PHZPp1zU2DaLGtezgovkBhgfhXTHJV9T7zCW971etzgxAtcgv3ud+/R5gsGm+W7\n2Oz/XhQ4CCFqzkrMFBjX58HBwQWf3e1+lvT4uCyNlR5f7nfgDcrzZyAGTKkexoiBm0JmINrNwrLe\nmIfc+8cVx7p/Ed+TsGce9Vy9e3g/p5rou9js/14UOAghas5KLGoU12fvTdK/fyRkX9zx3mdhxbMq\nPT7p76BQKJh0KmVK6arb3EBhxA0k/DMQUUmlUsYibZ4nuqDXvkA7k7Yx7JlHPVf/PfbhzHY0y3ex\n2f+9qMiVEEKIRAwNDdGTzbKLy1xRTCK1BUdq+ZrvyK/gpGC6xbfvFhwR5c0Y4ANYPIHN3yAnhiiP\nAgchVhit6rqII67P/YODCz7bTLzDIOqzW6twfCW/g207dvAI8G+ANJfZxmUsvoOTLGo8cNcwskAO\nw2rmuIEpbK7CJoPFe0jxq+5VvBqelbQx7JnHPdeP+X5+NeE96sFK/PdSlnpNbURtaKlCiLrS7GKv\nWtBIcWQlx3vFtirtl9/BkAOzDkypIud63zKGf6mizcD97pJGX0AD0Wag33hiytWUxJJJhYthzzzq\nuXriSO+zSsWRYa6HBx980LS3t5dEp+3tZnJyMvE14/rRTP9epHEQQtSFaha6Wi6Uc5qEFdSq1fFJ\nim1V2q9gQamxsTGzdetWV//gF1LuM6Wy3ifdn+2IwOJXXR2EbdLYxgLT2dZWUWXQuOcUZses9DlU\nUhk0DYsOHpr134uKXCnltBBCVJWpqSn27t3LqVOncNJZg5O++lqcpFJZYAeOFsLPR3GSYr/F/DJV\nMDLyQU6cOFHjlicjl8txbGIiNEn3rwH/KbAv1d7OpUuX6t/QGqGU00IIIarK0NAQTz31FIVCgeHh\nzTh1MJ8FvoajhXgfpYDCzw9wgoZgmSo4+Y1v1L7hCXnyxAlyLJR+5oC/Ddk39/bbdWxda6LAQQgh\nVgBeAOFMN79DPn8GZwj4O8Ili98l3I2RwxRraYqViAIHIYRYgWzYsIF8/jRr1vTDgsJaW2CZBAdx\nrocw10qqvb2OrWtNFDgIIZY9U1NT5HI5+nt76e/tJZfLMTWljARBgs/pnnvu4e/+7u/I50+Tcgtr\nOVsGJ5iIGpLnKrpPLX8fhw8fprOzc0HYA/BffPt+ym11JpXSd2Sp1EuFGbUhV4UQYgk0u12uWSj3\nnAqFghkZGTFW0coZVVgrbUZGRiLvMTo6WrRxesW0av37CHM9+O2YNuE1MlrhOyI7phBCVEiz1xJo\nFip9ToVCwbS3d7kBRMbdLNPe3hU62BYKBdPZ2eMGF7sMXGkgbVLY5oM0tv5EK39HlHJaCCEqJE5V\n/8Tx441pVBNS6XMaGhriRz/6Prncbnp6uujp6SKX282PfvR9hoaGFhx/4MABZmZmgK8CT+Dkf9zF\nHOv4G2zmSHP06AQjIyN1XyLQd6S6hHlwhBBCCIaGhhgfH0907IkTT+IMxf8ZmAEeB34deB6nLgbA\nBCdPPsV73/v+yABEND8VzzhYljViWdZXLMv6J8uy5izL+mjIMZ+2LOsFy7Lesizr65ZlXVed5goh\nxHxUSyAZ9XtOXgDxNzhWT38eiFOAxdtvX+Saa95Db29/XUSK+o5Ul8UsVWSBbwH/DmddZR6WZX0S\n+ATwSzji1jeBY5ZlyQMjhKg6Uar6zs5OHnjggcY2ron47Gc/SyqVqtlz2rFjG85QPOvuiarKmQNW\nMzt7BdPTO5mYOMZVV72b7u4rahZE6DtSXSoOHIwxDxtjftcY8xBghRzyG8DvG2OOGmO+DdwFXA3s\nXVpThRBiIUNDQzx37hy7cjmO9/RwvKeHXbkcz507p6lwl6mpKbZv3crs3BzX4ygQjgKkUpx86qmq\nPKfPfvazOO+S0+7V3yxzxg34s1G++eYbTEx8jauvvoazZ88uuT1+9B2pLlXVOFiWdS0wBEx6+4wx\nFyzLOgV8EPif1byfEEJAZWvxKxFPuPhNAvUc5ua49957q/Ls7rnnHmxm+UXgMGD4Fs5SxTOBu3qz\nEl6x7qJMEfhnjDHcfPOtvPDCP1R1UNd3pHpU21UxhBNyvhjY/6L7mRBCiDpTD1fBkydOsAf4U+AF\nLjPGHOEZKQ2wEfhl39kWzgyEo4EwZpaDBw9WpV2i+jSNq+LQoUP09fXN27d//37279/foBYJIYRY\nDEPAXwNTXGYD8DLjOMGBp3/4Q6Db/dmbhfgcpXDmJMePP1HXNi8Hjhw5wpEjR+bte/311+vejmoH\nDlM4344rmT/rcCXzBa0L+PznP6+y2kIIUQO27djB0YmJ0EWDXVVyFYTdowC8BuRyH2F8fJypqSnW\nrl3HzMyHcAIEgAkWzkCIMMJepn1ltetGVZcqjDE/wAke7vT2WZbVCwzjeHSEEELUmXq4CpLcY2ho\niHPnniOX24Vtfw0ndPkE8BjODIQXzrzKzp23VaVdovosJo9D1rKsjZZl3ezuWuv+/d3u378A/I5l\nWXssy/pJ4EvAj4GHqtNkIYQQlVAPV0HSe3gixR//+Ie0t7fjLFv8a/waiEymSzbJJmYxSxW34oSH\nXn7s/+ju/2/ALxpj/sCyrC7gT4ArgG8AHzHGvF2F9gohhFgE9XAVVHqPdmuWd7hMB+O8A1xmDtuC\np59+QjbJJmYxeRyOG2NSxhg7sP2i75hPGWOuNsZ0GWM+bIx5vrrNFkIIsZw5cOAAFy9d4jTwFrO8\nwyxnMFjGcO+991Z0La+Md29vf92yUa5kmsZVIYQQYuUQZxE9XoFFtCS4nMETXE5MHGXt2nWcO/ec\nZi5qgKpjCiGEWLaUqnI+TakmxtPMzMxw9dVXY1ltWFYbmUyGRx99tLGNbREUOAghhKg71So8VarK\nuXDuwhjb/SzH22/PceedH1bwUAUUOAghhKg79Sk8tYHSLMTjwBx33vkvpINYIgochBBC1J1qWURL\nVTnD5i7+lfv3N4C7ARvYU6zKuXbtOgUPi0DiSCGEEA2hGhbRw4cPu+LILZSyUR4Feillo/wicBan\nFkYpd+bMzBYOHjyo4lcVohkHIYQQyxZ/NsqenuP09BzHsmaB14HvuUd9BdhNmA5CNTEqR4GDEEKI\nZY03c3HhwnkuXDjPI488glM2yVNQfBcnX6GoBgochBBCtBR33HEHk5PHaG9P4SxbvEKUDkI1MSpH\ngYMQQoiW44477uDSpUsY8w6Fwgt0dnZCwMNRXQfHykGBgxBCiJYmTAeRy+1KnFlSKa3nI1eFEEKI\nlmexDg6ltF6IZhyEEEKICOJSWh88eLCxjWsQChyEEEKICOJSWq9UK6cCByGEEEIkRoGDEEIIEUFc\nSuuVauVU4CCEEEJE4BXjkpWzhAIHIYQQIoKlWjlbEdkxhRBCiBiqUYyrldCMgxBCCCESo8BBCCGE\nEIlR4CCEEEKIxChwEEIIIURiFDgIIYQQIjEKHIQQQgiRGAUOQgghhEiMAgchhBBCJEaBgxBCCCES\no8BBCCGEEIlR4CCEEEKIxChwEEIIIURiFDgIIYQQIjEKHIQQQgiRGAUOQgghhEiMAgchhBBCJEaB\ngxBCCCESo8BBCCGEEIlR4CCEEEKIxChwEEIIIURiFDgIIYQQIjEKHIQQQgiRGAUOQgghhEiMAgch\nhBBCJEaBgxBCCCESo8BBCCGEEIlR4CCEEEKIxChwEEIIIURiFDgIIYQQIjEKHIQQQgiRGAUOQggh\nhEiMAocacOTIkUY3oaq0Un9aqS+g/jQzrdQXUH9EiZoFDpZl/aplWT+wLGvGsqynLMv6qVrdq9lo\ntS9kK/WnlfoC6k8z00p9AfVHlKhJ4GBZ1r8E/iPwe8AtQB44ZlnWmlrcTwghhBD1oVYzDoeAPzHG\nfMkY813gV4C3gF+s0f2EEEIIUQeqHjhYltUGbAYmvX3GGAM8Anyw2vcTQgghRP1I1+CaawAbeDGw\n/0Xg+pDjOwC+853v1KApjeH111/nzJkzjW5G1Wil/rRSX0D9aWZaqS+g/jQrvrGzo173tJzJgCpe\n0LKuAv4J+KAx5pRv//8N7DDGfDBw/L8C/ntVGyGEEEKsLH7eGPMX9bhRLWYcXgFmgSsD+68EpkKO\nPwb8PPD/t3duoXZUdxj/fRGNNzRGE0/BK8ZKqpJItV5aNVVBaasiiPhiad98i77USh8qIgoKQbzE\nh4oRjS2oVbE1ihEFrakJmng3UYwaNI21TYih3mL892Gtg3Mms/eekLPPmXX4fjCcM3v9z8z6zreG\n9d9r1sz6EPhqCPUxxhhjpip7A0eR+tIJYdxHHAAkvQSsjIiFeV/ABuC2iLhl3E9ojDHGmAlhGCMO\nAIuAeyW9AqwiPWWxL3DvkM5njDHGmAlgKIlDRDyY39lwPekWxavA+RHx2TDOZ4wxxpiJYSi3Kowx\nxhgzNfFaFcYYY4xpjRMHY4wxxrRmXBIHSWdKelzSJ5K+k3RRQ8z1kjZK+kLScklzauXTJd0p6T+S\ntkl6WNLsWsxBkh6QtFXSFkl3S9pvPDTsih5JS/Ln1W1ZF/VIulbSKkmfS/pU0qOSftgQV4Q/bfSU\n4o+kKyW9lo+/VdIKSRfUYorwpY2eUnzpoe33ub6Lap8X488gPSX5I+mPDXV9uxZTjDeD9HTOm4jY\n7Q24gDQR8mLSOxwuqpVfA2wGfgWcADwGvA/sVYm5i/Quh7NJC2OtAF6oHedJYDVwMnAG8C6wdDw0\n7KKeJcATwCxgdt4OrMV0Qg+wDLgCmAucCPw912ufEv1pqacIf4Bf5rZ2DDAHuAH4Gphbmi8t9RTh\nS4OuU4D1wBpgUYnXTUs9xfhDWkDx9VpdZ5bqTQs9nfJmGI3yO3buaDcCV1f2DwC+BC6r7H8NXFKJ\nOS4f6yd5f27eP6kScz7wLTAyxIusSc8S4JE+f9NlPYfk8/5sivjTpKdkf/4L/LZ0X3roKc4XYH9g\nHXAO8BxjO9ri/Bmgpxh/SB3t6j7lRXnTQk+nvBn6HAdJRwMjjF306nNgJd8venUy6dHQasw60kuj\nRmNOA7ZExJrK4Z8BAjh1WPXvwwKlofK1khZLmlkp+zHd1TMjn2MzTAl/xuipUJQ/kqZJupz0vpMV\npftS11MpKsoX4E7gbxHxbPXDgv1p1FOhJH+OVbqd/L6kpZIOh6K9adRToTPeDOsFUFVGSBVrWvRq\nJP9+KPBNNrdXzAjw72phROyQtLkSM1E8CfwV+IA0LHsTsEzS6ZHSuBE6qEeSgFuBf0TE6P2zYv3p\noQcK8kfSCcA/Sa+N3Ub6xrBO0ukU6EsvPbm4GF+ylsuB+aROpk5x180APVCWPy8BvyGNnvwAuA54\nPre/4ryhWc8Lko6PiP/RMW8mInGYckTEg5XdtyS9Qbp/toA0/NdVFgM/An462RUZJxr1FObPWmAe\ncCBwKXCfpLMmt0q7RaOeiFhbki+SDiMlpedFxPbJrs/u0kZPSf5ERHVdhjclrQI+Ai4jtcGiGKBn\nSde8mYjHMTcBov+iV5uAvSQdMCCmPkN0D2AmzYtnTRgR8QFpca/RWbud0yPpDuAXwIKI+FelqEh/\n+ujZiS77ExHfRsT6iFgTEX8AXgMWUqgvffQ0xXbWF9LQ7yxgtaTtkraTJp0tlPQN6ZtcSf701ZNH\n78bQcX/qdd1Kmug3h0KvnSo1PU3lk+rN0BOHLHATcO7oZ1ncqXx/7/MV0gSNasxxwBGkYU/yzxmS\nTqoc/lxSA1nJJJKz+YOB0Q6sU3pyJ3sx8POI2FAtK9Gffnp6xHfanxrTgOkl+tKDacD0poKO+/IM\n6amd+aQRlHnAy8BSYF5ErKcsfwbpifofdNyfel33J3WiG6fCtVPR0/ilaNK92ZWZlL02YD9SQ5xP\nmrV5Vd4/PJf/jjS7+kJS430MeI+xj8YsJt2/WUDKjl9k50dJlpEa+ymk4el1wP3joaGtnlx2M6kR\nHpn/8S8D7wB7dk1PrscW4ExS9jm67V2JKcafQXpK8ge4Mes4kvTI2E2ki/+c0nwZpKckX/roqz+F\nUJQ//fSU5g9wC3BWrusZwHLSKNDBJXrTT08XvRkv0WeTOtgdte2eSsx1pEdkviCtGz6ndozpwO2k\n4ZdtwEPA7FrMDFKGvJXUefwJ2HcIJvbUQ5r09RQpo/2K9Dz0XcCsLurpoWMH8OtaXBH+DNJTkj/A\n3bl+X+b6Pk1OGkrzZZCeknzpo+9ZKolDaf7001OaP8BfgI9zW9sA/Bk4ulRv+unpojde5MoYY4wx\nrfFaFcYYY4xpjRMHY4wxxrTGiYMxxhhjWuPEwRhjjDGtceJgjDHGmNY4cTDGGGNMa5w4GGOMMaY1\nThyMMcYY0xonDsYYY4xpjRMHY4wxxrTGiYMxxhhjWvN/oMlsUg3YHIAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x5a5f3d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(cars[\"weight\"], cars[\"mpg\"], c='red')\n",
    "plt.scatter(cars[\"weight\"], predictions, c='blue')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "18.7809397346\n"
     ]
    }
   ],
   "source": [
    "lr = LinearRegression()\n",
    "lr.fit(cars[[\"weight\"]], cars[\"mpg\"])\n",
    "predictions = lr.predict(cars[[\"weight\"]])\n",
    "from sklearn.metrics import mean_squared_error\n",
    "mse = mean_squared_error(cars[\"mpg\"], predictions)\n",
    "print(mse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4.33369815915\n"
     ]
    }
   ],
   "source": [
    "mse = mean_squared_error(cars[\"mpg\"], predictions)\n",
    "rmse = mse ** (0.5)\n",
    "print (rmse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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